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  • Title: Abnormal Brain Network Connectivity in a Triple-Network Model of Alzheimer's Disease.
    Author: Li C, Li Y, Zheng L, Zhu X, Shao B, Fan G, Liu T, Wang J, Alzheimer’s Disease Neuroimaging Initiative.
    Journal: J Alzheimers Dis; 2019; 69(1):237-252. PubMed ID: 30958354.
    Abstract:
    Resting-state fMRI studies have demonstrated that Alzheimer's disease (AD) is associated with aberrant organization and function of large-scale brain networks. However, the nature of the disruption of cross-network interactions in the key neurocognitive networks in the brain remains unclear. In this paper, we examined the 'triple-network model', including the default mode network (DMN), salience network (SN), and central executive network (CEN), to identify the cross-network interactions in late mild cognitive impairment (LMCI) and AD. With resting-state fMRI, we tested cross-network functional connectivity among the DMN, SN, and CEN in 33 AD patients, 24 LMCI, and 25 well-matched normal control subjects. Then, we identified the most influential brain regions affected by AD and LMCI. Finally, we investigated the relationship between aberrant functional connectivity and clinical cognitive dysfunction. We found the cross-network functional connectivity of the SN-centered 'triple-network model' was significantly impaired in the AD group and the alterations were negatively correlated with the Mini-Mental State Examination (MMSE) scores. For the LMCI group, the functional connectivity of the SN-centered 'triple-network model' also changed compared to AD; however, we found no correlation with MMSE score. As predicted, the abnormal connections among the three networks mainly overlap with the key nodes of the three networks. Overall, our findings suggested that the interactions of the SN-centered 'triple-network model' are impaired in AD patients and that these alterations contribute to the decline in cognitive function. This 'triple-network model' provides new insights into AD and provides more information about the dysregulation of brain networks in AD.
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